Verified React chart generation: select, validate, repair, render, and inspect charts through MCP.
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Enable or disable individual tools per connector, so you decide what your agents can and cannot do.
Managed credentials
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Usage analytics
See which tools your agents call, how often, and when, so you can understand usage patterns and catch anomalies.
Average 3.7/5 across 5 of 5 tools scored.
Each tool has a clearly distinct purpose: create, audit, explain, improve, and schema retrieval. No two tools overlap in their primary function, so an agent can easily select the right one.
All tool names follow a consistent verb-noun pattern in camelCase (auditChart, createChart, explainChart, getChartSchema, improveChart). The minor variation in 'getChartSchema' is still a verb+object, maintaining overall consistency.
Five tools is well-scoped for a charting domain, covering creation, analysis, improvement, explanation, and schema reference without bloat or redundancy.
The tool set covers the full lifecycle for charts: create, validate (within create), audit, improve, explain, and access schema for advanced configuration. No obvious missing operations for the stated purpose.
auditChartAudit chart quality and accessibilityARun design diagnostics plus accessibility and mobile audits, returning prioritized structured findings.
| Name | Required | Description | Default |
|---|---|---|---|
| props | Yes | ||
| component | Yes | ||
| viewportWidth | No |
| Name | Required | Description |
|---|---|---|
| status | Yes | |
| component | Yes | |
| surfaceVersion | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint, so the safety profile is covered. The description adds useful context about the audit scope and the structured, prioritized nature of findings, which goes beyond the annotations without contradicting them.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that delivers the core purpose and output format without any filler. Every word adds value, making it highly concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description gives a solid high-level overview and the output schema covers return values, but it lacks parameter-level context and does not elaborate on what 'design diagnostics' or 'accessibility audits' include. For a tool with a nested props object and optional viewportWidth, more input guidance would make it complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage, so the description must compensate for parameter meaning, but it does not. While 'component' and 'props' are reasonably self-explanatory and 'viewportWidth' hints at responsive/mobile testing, the description provides no explicit guidance on how these parameters should be supplied or how viewportWidth affects the audit.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'Run' and clearly identifies the resource 'chart quality and accessibility' with a concrete outcome ('prioritized structured findings'). This strongly distinguishes it from sibling tools like createChart, explainChart, getChartSchema, and improveChart.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly establishes the context for use: performing design, accessibility, and mobile audits on charts. It does not explicitly name alternatives or when-not conditions, but the sibling tool names make the differentiation clear, and the audit scope is well-defined.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
createChartCreate and prove a chartASelect, validate, diagnose, render, and prove a static-data Semiotic chart. This is the default public workflow.
| Name | Required | Description | Default |
|---|---|---|---|
| data | Yes | ||
| props | No | Optional props to merge over the selected chart recipe. | |
| theme | No | ||
| intent | No | ||
| audience | No | ||
| component | No | Optional chart preference; the fit-ranked result remains authoritative. |
| Name | Required | Description |
|---|---|---|
| status | Yes | |
| component | No | |
| surfaceVersion | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint and idempotentHint. The description adds value by outlining the multi-step behavior (validate, diagnose, prove) and clarifies that it works with static data, which is consistent with a non-destructive read operation. No contradiction, but it lacks deeper behavioral context such as data handling or error scenarios.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences with no redundant wording. It front-loads the tool's purpose and adds a concise usage context, achieving maximum clarity in minimal space.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (6 parameters, nested objects, output schema, and sibling tools), the description is far too thin. It omits practical guidance on how to use parameters, what 'prove' means, and how this tool compares to its siblings. The output schema exists but does not provide user-facing decision support.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is only 33%, and the description gives absolutely no parameter-specific guidance. It does not explain what 'data', 'props', 'theme', 'intent', 'audience', or 'component' mean for this workflow, so it fails to compensate for the low schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly lists the specific actions (select, validate, diagnose, render, and prove) and identifies the resource as a static-data Semiotic chart. It also positions this as the default public workflow, which differentiates it from specialized sibling tools like auditChart or explainChart.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
"This is the default public workflow" clearly indicates this is the primary tool for creating charts. However, it does not explicitly mention when not to use it or point to alternatives among the sibling tools, so it stops short of full usage guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
explainChartExplain a chart without pixelsBReturn reader grounding: chart description, communicative intent, and navigable data structure.
| Name | Required | Description | Default |
|---|---|---|---|
| props | Yes | ||
| component | Yes |
| Name | Required | Description |
|---|---|---|
| status | Yes | |
| grounding | Yes | |
| surfaceVersion | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate a read-only, idempotent, non-destructive operation. The description adds context by specifying the return payload (chart description, intent, data structure), which is consistent with the annotations. No contradictions found.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that efficiently conveys the tool's purpose and output components without redundancy. It is front-loaded with the verb 'Return'.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
While the output schema covers return values, the input parameters are completely undocumented. The description fails to explain how to specify the chart via 'component' and 'props', leaving the agent unable to invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, meaning the parameters 'component' and 'props' have no descriptions. The description does not clarify their meaning or provide examples. This is a critical gap since both are required.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'Return' and defines the resource as 'reader grounding' with three concrete outputs (chart description, communicative intent, navigable data structure). This clearly distinguishes it from siblings like createChart or getChartSchema, which focus on creation or schema retrieval.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided regarding when to use this tool versus alternatives. There is no mention of auditChart, getChartSchema, or other siblings, nor any conditions or prerequisites. The title hints at non-visual explanation, but the description lacks explicit usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
getChartSchemaGet a chart schemaAReturn canonical Semiotic prop-schema guidance for code editing and advanced configuration.
| Name | Required | Description | Default |
|---|---|---|---|
| component | No |
| Name | Required | Description |
|---|---|---|
| schema | No | |
| status | Yes | |
| component | No | |
| renderable | No | |
| accessibility | No | |
| surfaceVersion | Yes | |
| behaviorContracts | No | |
| availableComponents | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior, so the description does not need to restate these. It adds context by specifying that the output is 'canonical' guidance for Semiotic props, which goes beyond the annotations. No contradictions are present.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence that front-loads the core action ('Return...') and immediately adds purpose. It avoids redundancy and every phrase contributes meaning, making it appropriately concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has an output schema, so return format is covered, and annotations address safety. However, the description does not explain the optional 'component' parameter or the exact scope of 'chart schema,' leaving a notable gap for an agent to correctly invoke the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema lists a single 'component' parameter with no description, and the tool description does not mention this parameter at all. With 0% schema description coverage, the agent is left to infer the meaning of 'component' from the tool name and context, which is insufficient.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states that it returns 'canonical Semiotic prop-schema guidance,' which is a specific verb+resource combination. It distinguishes itself from siblings (audit, create, explain, improve) by focusing on schema retrieval for code editing and advanced configuration.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'for code editing and advanced configuration' implies a use case but does not explicitly state when to use this tool versus alternatives or mention any exclusion criteria. There is no reference to sibling tools or conditions under which other tools would be more appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
improveChartImprove an existing chartADiagnose a chart configuration, assess data fit, and propose repairs or variants.
| Name | Required | Description | Default |
|---|---|---|---|
| data | No | ||
| props | Yes | ||
| intent | No | ||
| component | Yes |
| Name | Required | Description |
|---|---|---|
| repair | Yes | |
| status | Yes | |
| variants | Yes | |
| component | Yes | |
| diagnostics | Yes | |
| surfaceVersion | Yes | |
| accessibilityRecommendation | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so safety is covered. The description adds that it proposes repairs/variants, giving some behavioral context, but doesn't detail how results are returned or whether it modifies anything (which it doesn't).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that front-loads the primary verb 'Diagnose' and contains no fluff. Every word contributes to the core purpose, making it highly concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 4 parameters, nested objects, and 0% schema coverage, the description is too sparse. It provides a high-level purpose but lacks sufficient detail about the inputs, process, or how to use it with the given parameters, despite having an output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not mention any of the four parameters (data, props, intent, component) or how they relate. No added parameter semantics beyond the schema's type-only definitions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb+resource: 'Diagnose a chart configuration, assess data fit, and propose repairs or variants.' This clearly distinguishes it from siblings like createChart (creating) and explainChart (explaining) by focusing on improving existing charts.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for existing charts that need improvement or repair, which sets it apart from createChart. It provides clear context but lacks explicit exclusions or named alternatives, which would earn a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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